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In this thesis I set out to explore Catholicism as a felt sense in Seamus Heaney's poetry from his first collection Death of a Naturalist (1966) to his last collection Human Chain (2010). Chapter One sets the scene of Heaney's Catholic sensibility, which was rooted in his childhood home of Mossbawn and formalised in the learning of the Catholic Catechism at school and his early exposure to writers such as Gerard Manley Hopkins and Patrick Kavanagh. Chapter Two identifies a Catholic sensibility in Heaney's use of sacramental language which consecrates the body as a unique good in Death of a Naturalist, manual labour in Door into the Dark, and place in Wintering Out. Chapter Three looks at Heaney's treatment of death in terms of Catholic ritual, including the veneration of relics (North), and the tactile piety which informs some of the elegies in Field Work and The Haw Lantern. Heaney's complex engagement with Catholicism in Station Island is the subject of Chapter Four, and I read the collection alongside his translation Sweeney Astray, published in the same year. Chapter Five explores Heaney's attempts to go beyond the limits of the material world (Seeing Things), and identifies this longing in the nature of love, and its demands, in The Spirit Level (exemplified in the saints) and Electric Light. In Chapter Six I argue that Catholicism operates in a more embedded way in the poems of District and Circle and Human Chain but remains as part of a sensibility which expands to include writers such as the classical poet Virgil. I identify four ways in which Catholicism operates in Heaney's poetry and draw attention to how these weave their way through the six chapters as: i) iconography, ii) sacramental vision, iii) poetic process, and iv) syntax and form.

InRethinking Childhood, twenty contributors, coming from the disciplines of anthropology, government, law, psychology, education, religion, philosophy, and sociology, provide a multidisciplinary view of childhood by listening and understanding the ways children shape their own futures. Taken together, these essays develop a new paradigm for understanding childhood as children experience these years. This paradigm challenges readers to develop fresh ways of listening to children's voices that enable both children and adults to cross the barriers of age, experience, and stereotyping that make communication difficult.

An unsolved problem with water vapor wind estimates from the upper-tropospheric 6.7-µm water vapor band on the Geostationary Operational Environmental Satellite (GOES) Imager (channel 3) is its exact placement in the vertical column. Satellite water vapor observations are known to be depth-averaged assessments of the upper-tropospheric moisture. Details about the effective averaging of upper-tropospheric observations, valid for GOES or those of other satellite platforms, are not retrieved as part of the observation. However, details about the vertical placement can be accurately estimated from forward radiative models that mimic the instrument spectral characteristics. A new method has been developed to assimilate satellite radiances or brightness temperatures directly into a numerical forecast model. A by-product of the new scheme is knowledge of the weighting functions that describe the assignment value given to each vertical layer. As a consequence, given water vapor wind data, these weighting functions allow the guessed wind field to be \"intelligently\" modified. In this study the vertical and horizontal characteristics of these weighting functions are examined. Statistics for a 16-day period are presented that show how weighted average wind components from the initial model forecast fields, computed using the weighting functions, compare with GOES water vapor wind observations. [PUBLICATION ABSTRACT]

Imager channel 3 (at 6.7 µm) on the Geostationary Operational Environmental Satellite (GOES) is particularly sensitive to water vapor in the atmosphere. Channel-3 data from both clear and cloudy regions are used in a new assimilation scheme to improve the initial upper-tropospheric moisture fields for modeling and numerical weather prediction purposes. In this assimilation, the navigated and calibrated radiance (brightness temperature) observations from GOES are used in combination with a forward radiative transmittance model and a numerical optimization procedure to produce modifications to the upper-tropospheric moisture field. All modifications are made proportional to the contribution weighting function, which is associated with the forward radiative model. Cloudy regions are given special consideration. When processed by a forward radiative transfer model, the assimilated moisture fields are shown to correlate better with GOES observations both initially and in 24- and 48-h forecasts. Additional merits of the proposed assimilation technique, which does not require an adjoint or linearization, are discussed. [PUBLICATION ABSTRACT]

The Mississippi River floodplain in the states of Arkansas, Tennessee, Mississippi, and Louisiana presents a readily discernible feature in weather satellite images. This floodplain appears in the spring and early summer as a daytime warm anomaly at infrared (IR) wavelengths and as a bright reflective area at visible wavelengths. Remnants of this feature can occasionally be identified at nighttime in the IR satellite images. During June the normalized difference vegetation index identifies major contrasts between this intense agricultural region and the surrounding mixed-forest region. This distinction and the homogeneity of the floodplain, with its alluvial soil, contrast with the encircling region, creating an agricultural region containing heat island features. Thirty years of climatological surface station data for the month of June reveal that the surface air temperatures in the floodplain experience less diurnal variation than those in the surrounding regions. This is primarily because nighttime minimums are warmer in the Mississippi River floodplain.

An unsolved problem with water vapor wind estimates from the upper-tropospheric 6.7-μm water vapor band on the Geostationary Operational Environmental Satellite (GOES) Imager (channel 3) is its exact placement in the vertical column. Satellite water vapor observations are known to be depth-averaged assessments of the uppertropospheric moisture. Details about the effective averaging of upper-tropospheric observations, valid for GOES or those of other satellite platforms, are not retrieved as part of the observation. However, details about the vertical placement can be accurately estimated from forward radiative models that mimic the instrument spectral characteristics. A new method has been developed to assimilate satellite radiances or brightness temperatures directly into a numerical forecast model. A by-product of the new scheme is knowledge of the weighting functions that describe the assignment value given to each vertical layer. As a consequence, given water vapor wind data, these weighting functions allow the guessed wind field to be ‘‘intelligently’’ modified. In this study the vertical and horizontal characteristics of these weighting functions are examined. Statistics for a 16-day period are presented that show how weighted average wind components from the initial model forecast fields, computed using the weighting functions, compare with GOES water vapor wind observations.

Imager channel 3 (at 6.7μm) on the Geostationary Operational Environmental Satellite (GOES) is particularly sensitive to water vapor in the atmosphere. Channel-3 data from both clear and cloudy regions are used in a new assimilation scheme to improve the initial upper-tropospheric moisture fields for modeling and numerical weather prediction purposes. In this assimilation, the navigated and calibrated radiance (brightness temperature) observations from GOES are used in combination with a forward radiative transmittance model and a numerical optimization procedure to produce modifications to the upper-tropospheric moisture field. All modifications are made proportional to the contribution weighting function, which is associated with the forward radiative model. Cloudy regions are given special consideration. When processed by a forward radiative transfer model, the assimilated moisture fields are shown to correlate better with GOES observations both initially and in 24- and 48-h forecasts. Additional merits of the proposed assimilation technique, which does not require an adjoint or linearization, are discussed.